---
title: "Untitled"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source: embed
---
```{r setup, message=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(p8105.datasets)
data("instacart")
```
Column {data-width=650}
-----------------------------------------------------------------------
### Chart A
```{r}
fruit_plot =
instacart %>%
filter(aisle == "fresh fruits") %>%
group_by(product_name) %>%
summarise(
n = n()
) %>%
filter(n > 2000) %>%
mutate(product_name = fct_reorder(product_name, n)) %>%
plot_ly(
x = ~product_name, y = ~n, type = "bar", color = ~product_name, colors = "viridis"
) %>%
layout(title = "Most Popular Fresh Fruits in Instacart")
fruit_plot
```
Column {data-width=350}
-----------------------------------------------------------------------
### Chart B
```{r}
whi_wine_plot = instacart %>%
filter(aisle == "white wines") %>%
group_by(order_dow) %>%
summarise(
average_hour = mean(order_hour_of_day)
) %>%
plot_ly(
x = ~order_dow, y = ~average_hour, type = "scatter", mode = "lines"
) %>%
layout(
title = "Average Order Hours of White Wines by Week",
xaxis = list(title = 'Days of the Week')
)
whi_wine_plot
```
### Chart C
```{r}
alcohol_plot = instacart %>%
filter(department == "alcohol") %>%
plot_ly(
x = ~aisle, y = ~order_hour_of_day, split = ~aisle, type = "violin", box = list(visible = T)
) %>%
layout(
title = "Distribution of Order Hour of Alocohols in Instacart",
xaxis = list(title = "Alcohol Types"),
yaxis = list(title = "Order Hourder of a Day")
)
alcohol_plot
```